Integration of storage and renewable energy into district heating systems: a review of modelling and optimization

Olsthoorn, Dave; Haghighat, Fariborz; Mirzaei, Parham A.

Abstract

The building and infrastructure sector is accountable for 46% of the total worldwide energy consumption. Most traditional energy sources such as coal or petroleum are among the non-renewable types and most likely to be depleted in the forthcoming decades. To address the current energy crisis, use of renewable energy such as solar sources and a considerable increase in energy efficiency are proposed as the potential solutions. District heating systems (DHS), in particular, has recently received more attention due to several advantages in energy production, distribution and consumption for the space heating.

This paper reviews the recent advancements in the energy production, modelling and optimization of the DHSs. A classification of energy sources is presented in terms of their sustainability and ease of integration to a DHS. Current modelling methods are further compared with respect to computational limitations, level of precision as well as the degree of certainty in the output level. Moreover, the recent studies of DHS are classified in accordance with the optimization objectives, including energy/exergy efficiency, cost, exergo-economic/thermo-economic and green-house gas (GHG) and pollutant production.

Citation

Olsthoorn, D., Haghighat, F., & Mirzaei, P. A. (2016). Integration of storage and renewable energy into district heating systems: a review of modelling and optimization. Solar Energy, 136, https://doi.org/10.1016/j.solener.2016.06.054

• Journal Article Type: Article
• Acceptance Date: Jun 21, 2016
• Online Publication Date: Jul 6, 2016
• Publication Date: Oct 15, 2016
• Deposit Date: Sep 26, 2016
• Journal: Solar Energy
• Print ISSN: 0038-092X
• Electronic ISSN: 1471-1257
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 136
• DOI: https://doi.org/10.1016/j.solener.2016.06.054
• Keywords: District heating; Optimization; Energy; Renewable; Sustainability; Modelling
• Public URL: https://nottingham-repository.worktribe.com/output/823414
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S0038092X16302353